Successful facial recognition technology is a dynamic and exciting possibility. Unfortunately many of its current applications have proven unreliable. Research has shown the methods used during most current applications are not adequate to acquire a high level of accuracy. Poor camera resolution, camera placement, and an insufficient number of cameras lead current facial recognition systems to produce unsatisfactory results during testing and deployment.
Face recognition has become one of the most important biometrics authentication technologies in the past few years. The Blue Line Security Solutions team has worked hard to overcome the two main challenges for accurate and fast face recognition, which are illumination and pose variation. Both of these issues can cause serious performance degradation in a face recognition system. Illumination can change the appearance of an object considerably, and in most cases these differences caused by significant changes in lighting conditions is what makes the task of facial recognition extremely difficult in some cases. The same statement is true for pose variation. These two problematic variables (pose and illumination) significantly cause the degradation of the 2D facial texture mapping of the human face and the overall reduction in the accuracy of the system.